Summary of the bioinformatic pipeline

Code

library(knitr)
library(targets)
library(MiscMetabar)
here::i_am("analysis/01_bioinformatics.qmd")

Code

d_pq <- tar_read("d_vs", store=here::here("_targets/"))

Code

tar_glimpse(script=here::here("_targets.R"), targets_only = TRUE, callr_arguments = list(show = FALSE))

Load phyloseq object from targets store

Code

d_pq <- tar_read("d_vs", store=here::here("_targets/"))

The {targets} package is at the core of this project. Please read the intro of the user manual if you don’t know {targets}.

The {targets} package store … targets in a folder and can load (tar_load()) and read (tar_read) object from this folder.

Sample data

Code

DT::datatable(d_pq@sam_data)

Sequences, samples and clusters across the pipeline

Code

formattable_pq(
    d_pq,
    "Type",
    min_nb_seq_taxa = 1000,
    taxonomic_levels=c("Order", "Family", "Genus"),
    log10trans = TRUE
  )

Cleaning suppress 0 taxa (  ) and 0 sample(s) (  ).

Number of non-matching ASV 0

Number of matching ASV 1147

Number of filtered-out ASV 1135

Number of kept ASV 12

Number of kept samples 2

Cleaning suppress 0 taxa and 0 samples.

Joining with `by = join_by(OTU)`

OTU	Order	Family	Genus	Mono	proportion_samp	nb_seq
Taxa_2	Glomerales	Claroideoglomeraceae	Claroideoglomus	4.36	1	4.36
Taxa_12	Glomerales	NA	NA	3.85	1	3.85
Taxa_21	NA	NA	NA	3.64	1	3.64
Taxa_3	Glomerales	Glomeraceae	Glomus	3.61	1	3.61
Taxa_5	Glomerales	Glomeraceae	Glomus	3.48	1	3.48
Taxa_17	Glomerales	Glomeraceae	Glomus	3.42	1	3.42
Taxa_15	NA	NA	NA	3.39	1	3.39
Taxa_13	Glomerales	Claroideoglomeraceae	Claroideoglomus	3.38	1	3.38
Taxa_23	Glomerales	Claroideoglomeraceae	Claroideoglomus	3.32	1	3.32
Taxa_19	NA	NA	NA	3.23	1	3.23
Taxa_41	Glomerales	Glomeraceae	Glomus	3.14	1	3.14
Taxa_42	Glomerales	NA	NA	3.05	1	3.05

All samples together
Per samples

Code

kable(tar_read(track_sequences_samples_clusters, store=here::here("_targets/")))

	nb_sequences	nb_clusters	nb_samples
Paired sequences	20790310	5610	452
Paired sequences without chimera	20503830	3746	452
Paired sequences without chimera and longer than 200bp	20495636	3708	452
ASV denoising	67803	3708	2
OTU after vsearch reclustering at 97%	67803	1147	2
OTU vs after mumu cleaning algorithm	67803	31	2
OTU vs + mumu + rarefaction by sequencing depth	4000	28	2

Code

tab_samp <- tar_read(track_by_samples, store=here::here("_targets/"))

for (li in names(tab_samp)) {
  print(knitr::kable(tab_samp[[li]], caption = li, format="html"))
  cat('\n<!-- -->\n\n')
}

samp_01158
	nb_sequences	nb_clusters	nb_samples
ASV denoising	33764	96	1
OTU after vsearch reclustering at 97%	33764	55	1
OTU vs after mumu cleaning algorithm	33764	19	1
OTU vs + mumu + rarefaction by sequencing depth	2000	14	1

samp_01159
	nb_sequences	nb_clusters	nb_samples
ASV denoising	34039	113	1
OTU after vsearch reclustering at 97%	34039	76	1
OTU vs after mumu cleaning algorithm	34039	28	1
OTU vs + mumu + rarefaction by sequencing depth	2000	24	1

Session Information

Session information are detailed below. More information about the machine, the system, as well as python and R packages, are available in the file data_final/information_run.txt .

Code

sessionInfo()

R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 12 (bookworm)

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0

locale:
 [1] LC_CTYPE=fr_FR.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=fr_FR.UTF-8        LC_COLLATE=fr_FR.UTF-8    
 [5] LC_MONETARY=fr_FR.UTF-8    LC_MESSAGES=fr_FR.UTF-8   
 [7] LC_PAPER=fr_FR.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C       

time zone: Europe/Paris
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
[1] MiscMetabar_0.10.1 purrr_1.0.2        dplyr_1.1.4        dada2_1.32.0      
[5] Rcpp_1.0.13        ggplot2_3.5.1      phyloseq_1.48.0    targets_1.8.0     
[9] knitr_1.48        

loaded via a namespace (and not attached):
  [1] bitops_1.0-9                deldir_2.0-4               
  [3] gridExtra_2.3               permute_0.9-7              
  [5] rlang_1.1.4                 magrittr_2.0.3             
  [7] ade4_1.7-22                 matrixStats_1.4.1          
  [9] compiler_4.4.1              mgcv_1.9-1                 
 [11] png_0.1-8                   callr_3.7.6                
 [13] vctrs_0.6.5                 reshape2_1.4.4             
 [15] stringr_1.5.1               pwalign_1.0.0              
 [17] pkgconfig_2.0.3             crayon_1.5.3               
 [19] fastmap_1.2.0               backports_1.5.0            
 [21] XVector_0.44.0              utf8_1.2.4                 
 [23] Rsamtools_2.20.0            rmarkdown_2.28             
 [25] UCSC.utils_1.0.0            ps_1.8.0                   
 [27] xfun_0.48                   cachem_1.1.0               
 [29] zlibbioc_1.50.0             GenomeInfoDb_1.40.1        
 [31] jsonlite_1.8.9              biomformat_1.32.0          
 [33] highr_0.11                  rhdf5filters_1.16.0        
 [35] DelayedArray_0.30.1         Rhdf5lib_1.26.0            
 [37] BiocParallel_1.38.0         jpeg_0.1-10                
 [39] parallel_4.4.1              cluster_2.1.6              
 [41] R6_2.5.1                    bslib_0.8.0                
 [43] RColorBrewer_1.1-3          stringi_1.8.4              
 [45] jquerylib_0.1.4             GenomicRanges_1.56.2       
 [47] SummarizedExperiment_1.34.0 iterators_1.0.14           
 [49] IRanges_2.38.1              Matrix_1.7-0               
 [51] splines_4.4.1               igraph_2.1.1               
 [53] tidyselect_1.2.1            viridis_0.6.5              
 [55] rstudioapi_0.17.1           abind_1.4-8                
 [57] yaml_2.3.10                 vegan_2.6-8                
 [59] codetools_0.2-20            hwriter_1.3.2.1            
 [61] processx_3.8.4              lattice_0.22-6             
 [63] tibble_3.2.1                plyr_1.8.9                 
 [65] Biobase_2.64.0              withr_3.0.1                
 [67] ShortRead_1.62.0            evaluate_1.0.1             
 [69] survival_3.7-0              RcppParallel_5.1.9         
 [71] formattable_0.2.1           Biostrings_2.72.1          
 [73] pillar_1.9.0                BiocManager_1.30.25        
 [75] MatrixGenerics_1.16.0       DT_0.33                    
 [77] renv_1.0.11                 foreach_1.5.2              
 [79] stats4_4.4.1                generics_0.1.3             
 [81] rprojroot_2.0.4             S4Vectors_0.42.1           
 [83] munsell_0.5.1               scales_1.3.0               
 [85] base64url_1.4               glue_1.8.0                 
 [87] tools_4.4.1                 interp_1.1-6               
 [89] data.table_1.16.2           GenomicAlignments_1.40.0   
 [91] visNetwork_2.1.2            rhdf5_2.48.0               
 [93] grid_4.4.1                  tidyr_1.3.1                
 [95] ape_5.8                     crosstalk_1.2.1            
 [97] latticeExtra_0.6-30         colorspace_2.1-1           
 [99] nlme_3.1-165                GenomeInfoDbData_1.2.12    
[101] cli_3.6.3                   fansi_1.0.6                
[103] viridisLite_0.4.2           S4Arrays_1.4.1             
[105] gtable_0.3.5                sass_0.4.9                 
[107] digest_0.6.37               BiocGenerics_0.50.0        
[109] SparseArray_1.4.8           htmlwidgets_1.6.4          
[111] htmltools_0.5.8.1           multtest_2.60.0            
[113] lifecycle_1.0.4             here_1.0.1                 
[115] httr_1.4.7                  secretbase_1.0.3           
[117] MASS_7.3-61

Citation

BibTeX citation:

@online{taudière2024,
  author = {Taudière, Adrien},
  title = {Bioinformatics Pipeline Summary},
  date = {2024-10-28},
  langid = {en}
}

For attribution, please cite this work as:

Taudière, Adrien. 2024. “Bioinformatics Pipeline Summary.” October 28, 2024.